技术领域technical field
本发明涉及一种升降(“hoisting”)装备的预测性维护，特别是起重机(“crane”)的预测性维护。The present invention relates to predictive maintenance of lifting ("hoisting") equipment, in particular cranes ("cranes").
背景技术Background technique
背景技术的以下说明可以包括在本发明之前的相关技术未知的但由本发明提供的见解、发现、理解或者公开、或者与公开的关联之处。下文可以特别指出本发明的一些这样的贡献，然而本发明的其它这样的贡献将通过其上下文而显而易见。The following description of background art may include insights, discoveries, understandings or disclosures provided by the present invention, or connections to the disclosures, that were not known to the relevant art prior to the present invention but are provided by the present invention. Some such contributions of the invention may be pointed out in particular below, whereas other such contributions of the invention will be apparent from their context.
如今，升降装置或者起重机广泛应用于机械、化学、制造、加工、建筑和冶炼工业以及遍及世界的船坞或者港口和码头。高架起重机，也称为桥式起重机，是钩线机制沿着水平横梁运行而水平横梁自身则沿着两个相隔很远的轨道运行的起重机类型。钩线机制可以包含沿着水平横梁移动的滑车以及安排在滑车上以提升物体的升降机。通常，高架起重机是在长厂房中并且沿着厂房的两面长墙沿着轨道运行。它与龙门起重机相似。高架起重机通常由单横梁或者双横梁结构组成。它们可以使用通常的钢梁或者更复杂的箱形梁类型来建造。大多数升降机使用某种滑轮系统；滑轮是特别设计用于引导绳索、缆线、皮带或者链条的轮子，并且它们常常安装在轴上从而允许轮子自由旋转。这些滑轮可以安装到使单元旋转从而控制缆线供给的发动机上。升降机可以是将电发动机用作提升发动机的电动升降机，例如电动链式升降机、电动钢索升降机和电动升降带。升降装备可以包括用于装有发动机的滑轮单元、发动机电发动机自身和安装在滑车上的滑轮外壳的任何控制。控制可以包括多种启用软启动并且减小影响起重机和结构的应力的电路系统，例如用于控制升降机的操作(例如，提升的速度和方向)的逆变器。Today, lifting devices or cranes are widely used in the mechanical, chemical, manufacturing, process, construction and metallurgical industries as well as in shipyards or ports and terminals throughout the world. Overhead cranes, also known as bridge cranes, are types of cranes in which the hook-line mechanism runs along a horizontal beam which itself runs along two widely spaced rails. The hook line mechanism may consist of a trolley moving along the horizontal beam and a lift arranged on the trolley to lift the object. Typically, the overhead crane is in a long building and runs along rails along the two long walls of the building. It is similar to a gantry crane. Overhead cranes usually consist of single or double beam structures. They can be built using the usual steel girders or more complex box girder types. Most lifts use some sort of pulley system; pulleys are wheels specially designed to guide ropes, cables, belts, or chains, and they are often mounted on axles to allow the wheels to spin freely. These pulleys can be mounted to motors that rotate the unit to control the cable feed. The lift may be an electric lift using an electric motor as the lifting motor, such as electric chain lifts, electric wire rope lifts and electric belt lifts. The lifting equipment may include any controls for the pulley unit housing the motor, the motor itself and the pulley housing mounted on the trolley. Controls may include various circuitry that enables soft starting and reduces stress affecting the hoist and structure, such as an inverter for controlling the operation of the hoist (eg, speed and direction of hoisting).
就经济和安全性两方面而言，希望例如桥式起重机和龙门起重机的升降装置具有良好状态。升降装置的故障，例如在其刹车中的故障，可能会导致荷重坠落，这可能会造成升降装置损坏和/或造成对在升降装置附近的工作人员的危害。在维护期间，升降装置没有用于生产。从经济角度来看，例如升降装置这样的昂贵机械的停工时间应该保持尽可能地短和少。Lifting devices such as overhead cranes and gantry cranes are expected to be in good condition both in terms of economy and safety. A failure of the lifting device, for example in its brakes, may cause the load to fall, which may cause damage to the lifting device and/or cause a hazard to persons working in the vicinity of the lifting device. During the maintenance period, the lifting device was not used for production. From an economic point of view, the downtime of expensive machinery such as lifting devices should be kept as short and low as possible.
升降装置的维护需要可以在广阔地理区域内维修升降装置的训练有素的人员。由于能够胜任的维护人员数量有限，所以在检测到升降装置需要维护(例如在发生故障的情况下)至维修升降装置的维护人员到达之间可能存在一些延迟。Lift maintenance requires trained personnel who can service lifts over a wide geographic area. Due to the limited number of competent maintenance personnel, there may be some delay between the detection that the lifting device requires maintenance, for example in the event of a breakdown, and the arrival of the maintenance personnel to repair the lifting device.
升降装置的维护计划包括规定在维护期间要执行的操作的预先计划的维护。维护计划试图最小化在计划的维护之间的升降装置故障，并且从而最小化停工时间。A maintenance plan for a lift includes pre-planned maintenance specifying the operations to be performed during the maintenance period. The maintenance plan attempts to minimize hoist failures between planned maintenance, and thereby minimize downtime.
然而，在计划的维护之间仍然可能会有故障，因此需要维护人员更多的检查并且减少升降装置的正常运行时间。这些故障有可能是原生的，从而使得维护人员在计划的维护期间难以检测到这些故障。难点可能在于检测可能存在的故障，这些故障需要不合比例的时间才能发现，如果存在任何待发现的故障的话。照此，与升降装置停工时间的成本相比，在维护期间花在检测故障上的额外时间可能效率很低。检测故障的难点还可能在于，通过人眼或者通过检查升降装置的维护人员携带的常规维护装备不可能检测到故障。However, failures may still occur between planned maintenance, thus requiring more inspection by maintenance personnel and reducing the uptime of the hoist. These failures may be native, making them difficult for maintenance personnel to detect during planned maintenance. The difficulty may lie in detecting possible faults that take a disproportionate amount of time to discover, if any. As such, the extra time spent detecting faults during maintenance may be inefficient compared to the cost of hoist downtime. Detecting faults can also be difficult in that they are impossible to detect by human eyes or by conventional maintenance equipment carried by maintenance personnel inspecting the lift.
在起重机制造和使用中的持续性挑战在于如何利用有限的维护预算在较长服务期间内保持起重机的操作安全。A continuing challenge in the manufacture and use of cranes is how to maintain the operational safety of the cranes over a long service period with a limited maintenance budget.
发明内容Contents of the invention
根据本发明的方面，提供一种升降装备特别是起重机的预测性维护方法，包括：According to an aspect of the present invention, there is provided a predictive maintenance method for lifting equipment, especially a crane, comprising:
在维护中心处自动收集关于远程升降装备的至少一个组件的诊断数据，以及可选地收集关于该远程升降装备的操作环境的传感器数据；automatically collecting diagnostic data about at least one component of the remote lifting equipment, and optionally sensor data about an operating environment of the remote lifting equipment, at the maintenance center;
提供该远程升降装备的配置数据；Provide the configuration data of the remote lifting equipment;
提供关于该远程升降装备的至少一个组件的可靠性数据；providing reliability data regarding at least one component of the remote lifting equipment;
基于该诊断数据、配置数据、可靠性数据并且可选地基于该操作环境数据，自动生成最优化在该升降装备的寿命周期内的升降装备的维护成本和可靠性的维护计划。Based on the diagnostic data, configuration data, reliability data, and optionally based on the operating environment data, a maintenance plan is automatically generated that optimizes maintenance costs and reliability of the lifting equipment over the life cycle of the lifting equipment.
根据实施例，自动生成包括：According to an embodiment, automatic generation includes:
针对维护动作和计划的多个不同结合估计该远程装备的可靠性和维护成本；Estimate the reliability and maintenance cost of the remote equipment for different combinations of maintenance actions and schedules;
从该多个结合选择最有可能最优化在该远程升降装备的寿命周期内的该远程升降装备的维护成本和可靠性的维护动作和计划的结合。A combination of maintenance actions and plans is selected from the plurality of combinations that is most likely to optimize maintenance costs and reliability of the remote lifting equipment over the life cycle of the remote lifting equipment.
根据实施例，该自动生成包括：利用基于从多个远程设备收集到的历史数据而维护的设备类型特定的可靠性数据并且利用收集到的信息来最优化个体装备的本地维护。According to an embodiment, the automatic generation includes utilizing device type specific reliability data maintained based on historical data collected from a plurality of remote devices and using the collected information to optimize local maintenance of individual equipment.
根据实施例，该选择包括：选择估计的、提供在成本与可靠性或安全性之间最佳折衷的维护动作的结合。According to an embodiment, the selection comprises: selecting an estimated combination of maintenance actions that provides an optimal compromise between cost and reliability or safety.
根据实施例，该方法包括：在自动生成最优化的维护计划之后，手工调整该维护计划。According to an embodiment, the method comprises: after automatically generating the optimized maintenance plan, manually adjusting the maintenance plan.
根据实施例，该方法包括：在数据库中维护客户特定的数据，该客户特定的数据包括该远程装备的一个或多个配置数据、该远程升降装备的类型、该远程升降装备的组件的类型、客户偏好、设计的使用配置文件。According to an embodiment, the method comprises: maintaining customer-specific data in a database, the customer-specific data comprising one or more configuration data of the remote equipment, the type of remote lifting equipment, the type of components of the remote lifting equipment, Customer preferences, designed usage profiles.
根据实施例，该方法包括：在数据库中维护装备类型特定的数据，该装备类型特定的数据包括针对每个类型的装备和/或组件的参数、特征和/或可靠性数据。According to an embodiment, the method comprises maintaining equipment type specific data in a database, the equipment type specific data comprising parameter, characteristic and/or reliability data for each type of equipment and/or components.
根据实施例，收集到的诊断数据包括来自所述远程升降装备的操作、使用或者状态数据，优选地是以下的一个或多个：升降机启动、升降机工作周期、升降机运行小时数、升降机装载数据、升降机超温发生次数、过载、紧急停止、关于任何超出该远程升降装备的性能限制的事件发生的数据。According to an embodiment, the collected diagnostic data comprises operation, usage or status data from said remote lifting equipment, preferably one or more of the following: lift activation, lift duty cycle, lift operating hours, lift loading data, Number of occurrences of lift over-temperature, overload, emergency stop, data on any occurrence of events that exceed the performance limits of the remote lift equipment.
根据实施例，关于该远程升降装备的操作环境的传感器数据包括温度、湿度、腐蚀和加速度中的一个或多个。According to an embodiment, the sensor data about the operating environment of the remote lifting equipment includes one or more of temperature, humidity, corrosion, and acceleration.
根据实施例，关于该远程升降装备的操作环境的传感器数据包括对该远程升降装备的外部冲击和碰撞的数据，优选地在笛卡尔坐标轴的x、y和z方向上三维地测量加速度。According to an embodiment, the sensor data about the operating environment of the remote lifting equipment comprises data of external shocks and collisions to the remote lifting equipment, accelerations are preferably measured three-dimensionally in the x, y and z directions of Cartesian coordinate axes.
根据实施例，关于该远程升降装备的操作环境的传感器数据包括：表示环境对该远程升降装备的电气装置的腐蚀作用的数据。According to an embodiment, the sensor data about the operating environment of the remote lifting equipment comprises data indicative of a corrosive effect of the environment on electrical installations of the remote lifting equipment.
根据实施例，该方法包括：在估计该远程升降装备的可靠性时，至少在如果观察到异常环境中的操作时，将操作环境数据纳入考虑。According to an embodiment, the method comprises taking into account operating environment data when estimating the reliability of the remote lifting equipment, at least if operation in an abnormal environment is observed.
本发明的另一方面为一种维护系统，包括被配置为执行根据本发明的第一方面的方法的部件。Another aspect of the invention is a maintenance system comprising means configured to perform the method according to the first aspect of the invention.
根据实施例，该系统包括至少一个计算机和包含计算机程序代码的至少一个存储器，该至少一个存储器和该计算机程序代码被配置为至少利用该计算机引起设备至少执行根据本发明第一方面的方法。According to an embodiment, the system comprises at least one computer and at least one memory containing computer program code configured to cause the device at least with the computer to perform at least the method according to the first aspect of the invention.
本发明的其它方面为一种包括可执行代码的计算机程序，当执行该可执行代码时，该可执行代码引起执行根据本发明第一方面的方法的功能。A further aspect of the invention is a computer program comprising executable code which, when executed, causes the functions of the method according to the first aspect of the invention to be performed.
附图说明Description of drawings
在下文中，将参照附图通过示例性实施例来更详细地描述本发明，其中：In the following, the invention will be described in more detail by way of exemplary embodiments with reference to the accompanying drawings, in which:
图1示出根据实施例的自动最优化的装备特定的预测性维护概念的示例；Figure 1 shows an example of an automatically optimized equipment-specific predictive maintenance concept according to an embodiment;
图2示出高架起重机的示例；Figure 2 shows an example of an overhead crane;
图3示出根据实施例的集中式维护系统106的示例；Figure 3 shows an example of a centralized maintenance system 106 according to an embodiment;
图4是示出提供服务或者维护计划的示例的流程图；FIG. 4 is a flowchart illustrating an example of providing a service or maintenance plan;
图5示出针对在装备未来寿命周期上计划的N个连续维护动作的估计的可靠性和估计的累计成本；Figure 5 shows the estimated reliability and estimated cumulative cost for N consecutive maintenance actions planned over the future life cycle of the equipment;
图6示出可靠性数据的更新。Fig. 6 shows updating of reliability data.
具体实施方式Detailed ways
以下实施例是示例性的。虽然说明书在若干位置处可能提及“一”、“一个”或者“一些”实施例，但这不一定意味着每次这样的提及都是指相同实施例，或者特征仅应用于单个实施例。也可以结合不同实施例的单个特征从而提供其它实施例。The following examples are exemplary. Although the specification may refer to "an", "an" or "some" embodiments in several places, this does not necessarily mean that each such reference refers to the same embodiment, or that the feature applies to only a single embodiment . Individual features of different embodiments may also be combined to provide other embodiments.
本发明的一个方面在于提供一种旨在具有减少的寿命周期成本以及增加的可靠性和安全性的自动最优化的装备特定的预测性维护方案。预测性维护方案可以是自主学习方案，其中，最优化的学习是基于由多个(例如，整个机群)装备提供的信息，从而使得利用提供的信息来最优化个体装备的维护。这使得在出售时或者在寿命周期之初便已经能够更准确地预测装备的寿命周期。可以说，预测性维护现在是从维护服务提供方的角度来考虑。维护服务提供方能够从更大数量的装备搜集信息和经验并且利用收集到的信息来最优化个体装备的本地维护。传统上，预测性维护和维护的适时(“right-time”)实现已经从工厂操作员的角度考虑，并且目标已经是最优化特定有限实体(工厂操作员的装备)。本发明的实施例可以进一步允许生成用于特定时刻的理论上的可靠性分析。An aspect of the present invention is to provide an automatically optimized equipment specific predictive maintenance scheme aimed at having reduced life cycle costs and increased reliability and safety. A predictive maintenance scheme may be a self-learning scheme, where optimal learning is based on information provided by multiple (eg, entire fleets) of equipment such that the provided information is used to optimize maintenance of individual equipment. This makes it possible to more accurately predict the life cycle of equipment at the point of sale or already at the beginning of the life cycle. It can be said that predictive maintenance is now considered from the perspective of maintenance service providers. Maintenance service providers are able to gather information and experience from a larger amount of equipment and use the gathered information to optimize local maintenance of individual equipment. Traditionally, predictive maintenance and just-in-time ("right-time") implementation of maintenance have been considered from the perspective of the plant operator, and the goal has been to optimize a specific finite entity (the plant operator's equipment). Embodiments of the present invention may further allow generating a theoretical reliability analysis for a particular moment in time.
一方面是提供一种自动最优化的装备特定的预测性维护系统，对该系统输入客户特定的信息，并且该系统自动利用从多个装备(例如，整个装备机群)收集的装备特定的信息来生成最优化的维护计划。One aspect is to provide an automatically optimized equipment-specific predictive maintenance system into which customer-specific information is input and which automatically utilizes equipment-specific information collected from multiple equipment (e.g., an entire fleet of equipment) to Generate optimized maintenance plans.
最优化的维护计划包括预先计划的维护，预先计划的维护规定在延长时间期间上(优选地在装备的寿命周期上)的维护期间里将要执行的操作。An optimized maintenance plan includes pre-planned maintenance specifying operations to be performed during a maintenance period over an extended period of time, preferably over the life cycle of the equipment.
图1示出根据实施例的自动最优化的装备特定的预测性维护概念的示例。集中式维护系统106优选地由维护服务提供方操作。集中式维护系统106可以安排为在(多个)通信系统104上与多个装备1021,1022,1023,…,102N通信。装备1021,1022,1023,…,102N可以位于正在操作中或者等待安装或运输的多个维护客户的处所，或者正在运往客户的处所。客户的处所可以包括：机械、化学、制造、加工、建筑和冶炼车间或工厂，以及遍及世界的船坞或者港口和码头。(多个)通信系统可以包括使得数据能够从装备1021,1022,1023,…,102N向集中式维护传输的任何通信系统或者任何通信系统的结合。Fig. 1 shows an example of an automatically optimized equipment-specific predictive maintenance concept according to an embodiment. The centralized maintenance system 106 is preferably operated by a maintenance service provider. The centralized maintenance system 106 may be arranged to communicate with a plurality of equipment 1021 , 1022 , 1023 , . . . , 102N over the communication system(s) 104 . The equipment 1021 , 1022 , 1023 , . . . , 102N may be located at a plurality of maintenance customer premises that are in operation or awaiting installation or shipment, or are being shipped to customer premises. Customer premises can include: mechanical, chemical, manufacturing, process, construction and metallurgical plants or factories, as well as shipyards or ports and terminals throughout the world. The communication system(s) may comprise any communication system or any combination of communication systems enabling data transmission from the equipment 1021 , 1022 , 1023 , . . . , 102N to the centralized maintenance.
多个装备，也称为装备1021,1022,1023,…,102N的机群，可以(至少主要地)包括升降装置，例如起重机1…N。不同类型的起重机的示例包括：高架起重机、桥式起重机、龙门起重机、塔式起重机和港口起重机。然而，多个装备还可以额外地包括其它装备，例如机械工具。A plurality of installations, also referred to as afleet of installations 1021 , 1022 , 1023 , . Examples of different types of cranes include: overhead cranes, bridge cranes, gantry cranes, tower cranes and harbor cranes. However, the plurality of equipment may also additionally include other equipment, such as machine tools.
作为装备1021,1022,1023,…,102N的示例，图2示出示例性的高架起重机。高架起重机102，也称为桥式起重机，是钩线机制122,124,128沿着水平横梁126运行而水平横梁126自身则沿着两个相隔很远的轨道132运行的起重机类型。钩线机制可以包含沿着水平横梁126移动的滑车122以及安排在滑车122上以提升物体的升降机124,128。通常，高架起重机是在长厂房中并且沿着厂房的两面长墙沿着轨道132运行。它与龙门起重机相似。高架起重机通常由单横梁或者双横梁结构126组成。它们可以使用通常的钢梁或者更复杂的箱形梁类型来建造。大多数升降机124,126使用某种滑轮系统；滑轮是特别设计用于引导绳索、缆线、皮带或者链条的轮子，并且它们常常安装在轴上从而允许轮子自由旋转。这些滑轮可以安装到使单元旋转从而控制缆线供给的发动机上。升降机可以是将电发动机用作提升发动机的电动升降机，例如电动链式升降机、电动钢索升降机和电动升降带。升降装备128可以包括：用于装有发动机的滑轮单元、发动机电发动机自身和安装在滑车上的滑轮外壳的任何控制。控制可以包括多种启用软启动并且减小影响起重机和结构的应力的电路系统，例如用于控制升降机的操作(例如，提升速度和方向)的逆变器。升降机还可以提供有传感器，传感器搜集数据起重机组件的诊断数据，以及可选地与起重机的操作环境有关的数据。如上文参照图1所讨论的，存在起重机装备102可以通过(多个)通信系统104向集中式维护系统106通信数据的许多显而易见的方式。在图2中示出示例实施例，其中，升降机128可以使用本地客户网络134(例如有线或无线局域网(LAN))进行通信。客户网络134可以提供向互联网或者任何其它数据通信网络的接入网。可以提供本地数据收集系统或者单元136来收集诊断数据并且可选地收集环境数据，并且大概在预处理之后向集中式维护系统106发送数据。可以存在附接至起重机102、用于向集中式维护系统传送信息的主固定连接和副无线连接(即，3G、GPRS或者卫星)。在起重机102或数据收集系统136与集中式维护系统106之间可以优选地使用安全连接，例如VPN连接。As an example of equipment 1021 , 1022 , 1023 , . . . , 102N , FIG. 2 shows an exemplary overhead crane. The overhead crane 102 , also known as an overhead crane, is a type of crane in which the hook line mechanism 122 , 124 , 128 runs along a horizontal beam 126 which itself runs along two widely spaced rails 132 . The hooking line mechanism may include a trolley 122 that moves along a horizontal beam 126 and elevators 124, 128 arranged on the trolley 122 to lift objects. Typically, the overhead crane is in the long building and runs along track 132 along the two long walls of the building. It is similar to a gantry crane. Overhead cranes typically consist of a single beam or double beam structure 126 . They can be built using the usual steel girders or more complex box girder types. Most lifts 124, 126 use some sort of pulley system; pulleys are wheels specially designed to guide ropes, cables, belts or chains, and they are often mounted on axles to allow the wheels to rotate freely. These pulleys can be mounted to motors that rotate the unit to control the cable feed. The lift may be an electric lift using an electric motor as the lifting motor, such as electric chain lifts, electric wire rope lifts and electric belt lifts. Lifting equipment 128 may include any controls for the pulley unit housing the motor, the motor itself, and the pulley housing mounted on the trolley. Controls may include various circuitry that enables soft starting and reduces stress affecting the hoist and structure, such as an inverter for controlling the operation of the elevator (eg, hoisting speed and direction). The hoist may also be provided with sensors that collect diagnostic data of the hoist components, and optionally data relating to the operating environment of the hoist. As discussed above with reference to FIG. 1 , there are a number of obvious ways in which the crane rig 102 may communicate data through the communication system(s) 104 to the centralized maintenance system 106 . An example embodiment is shown in FIG. 2, where elevator 128 may communicate using a local customer network 134, such as a wired or wireless local area network (LAN). Customer network 134 may provide access to the Internet or any other data communications network. A local data collection system or unit 136 may be provided to collect diagnostic data and optionally environmental data and send the data to the centralized maintenance system 106, presumably after pre-processing. There may be a primary fixed connection and a secondary wireless connection (ie 3G, GPRS or satellite) attached to the crane 102 for transferring information to the centralized maintenance system. A secure connection, such as a VPN connection, may preferably be used between the crane 102 or data collection system 136 and the centralized maintenance system 106 .
收集到的诊断数据可以包含来自起重机102的任何操作、使用或者状态数据。例如，收集到的数据可以包含以下的一个或多个：升降机启动(周期的和/或累计的)、升降机工作周期(周期的和/或累计的)、升降机运行小时数(周期的和/或累计的)、升降机装载数据、升降机超温发生次数(周期的和/或累计的)、过载(周期的和/或累计的)、紧急停止(周期的和/或累计的)、关于任何超出起重机性能限制的事件发生的数据、关于升降机的振动、加速度、速度或位移的信息等。这可以由升降机的控制部分连同与起重机的控制有关的多种传感器一起来提供。这样的传感器的示例包括：电发动机的过热传感器和用于升降机的荷重运动控制的加速度传感器。还可以提供不直接与起重机的控制有关的传感器。这样的传感器的示例是安排为监视起重机环境的环境传感器128。起重机(特别是升降机的电气单元)的使用寿命和维护需要深受起重机的环境影响。照此，通过位于电气单元处的传感器对环境的一个或多个特性的测量来提供在起重机实际环境中的期望使用寿命和维护需要的确定。环境传感器128的示例包括温度传感器、湿度传感器、腐蚀传感器、加速度传感器以及其任何结合。环境的温度、湿度和腐蚀特性对电气部分的可靠性和使用寿命具有显著影响。加速计可以监视对起重机的外部冲击和影响，冲击和影响造成损坏，缩短起重机的机械和/或电气组件的使用寿命。可以对每个监视的环境参数规定范围。可以在范围内和/或在范围外测量参数。当在范围内测量参数时，可以获得满足起重机使用说明的操作环境的信息。另一方面，当在范围外测量参数时，可以获得不满足使用说明的起重机的信息和/或在异常环境中(即，在规定起重机的不规则使用的环境中)操作的起重机的信息。在后一种情况下，在预测维护需要时可以将特殊环境纳入考虑。为了更详细地说明环境传感器布置，通过引用的方式将由相同申请人提交的共同未决专利申请FI20125829并入本文。The collected diagnostic data may include any operational, usage, or status data from the crane 102 . For example, collected data may include one or more of the following: lift starts (periodic and/or cumulative), lift duty cycles (periodic and/or cumulative), lift operating hours (periodic and/or cumulative), lift loading data, number of lift overtemperature occurrences (periodic and/or cumulative), overload (periodic and/or cumulative), emergency stop (periodic and/or cumulative), information on any Data on the occurrence of performance-limiting events, information on vibrations, accelerations, velocities or displacements of the lift, etc. This can be provided by the control part of the elevator together with various sensors related to the control of the crane. Examples of such sensors include overheating sensors of electric motors and acceleration sensors for load motion control of elevators. It is also possible to provide sensors not directly related to the control of the crane. An example of such a sensor is the environment sensor 128 arranged to monitor the environment of the crane. The service life and maintenance needs of a crane (especially the electrical unit of a lift) are strongly influenced by the environment of the crane. As such, measurement of one or more characteristics of the environment by sensors located at the electrical unit provides a determination of expected service life and maintenance needs in the actual environment of the crane. Examples of environmental sensors 128 include temperature sensors, humidity sensors, corrosion sensors, acceleration sensors, and any combination thereof. The temperature, humidity and corrosive characteristics of the environment have a significant impact on the reliability and service life of electrical parts. Accelerometers can monitor external shocks and impacts to the crane, which can cause damage and shorten the life of the crane's mechanical and/or electrical components. Ranges may be specified for each monitored environmental parameter. Parameters can be measured in-range and/or out-of-range. When parameters are measured within ranges, information on the operating environment that satisfies the crane's operating instructions can be obtained. On the other hand, when parameters are measured out of range, information can be obtained on cranes that do not meet the instructions for use and/or on cranes operating in abnormal environments, ie in environments that prescribe irregular use of the cranes. In the latter case, special circumstances can be taken into account when predicting maintenance needs. In order to describe the environmental sensor arrangement in more detail, the co-pending patent application FI20125829 filed by the same applicant is hereby incorporated by reference.
图3示出根据实施例的集中式维护系统106的示例。集中式维护系统106优选地由维护服务提供方操作。集中式维护系统106可以提供有通信接口302，通信接口302被安排为在通信系统104上与多个1021,1022,1023,…,102N通信并且可选地与任何其它数据系统通信。通信接口106可以表示可以用于在每个特定应用中的通信的任何(多个)装置和功能。从多个装备1021,1022,1023,…,102N接收的数据可以被收集至装备特定的历史数据库306。数据库306可以包含对每个特定装备在延长时间周期内(优选地，在装备的整个寿命周期内)收集到的使用、诊断和/或环境数据。图3所示的数据收集系统304一般可以表示可以用在数据收集中的任何(多个)装置和功能。FIG. 3 shows an example of a centralized maintenance system 106 according to an embodiment. The centralized maintenance system 106 is preferably operated by a maintenance service provider. The centralized maintenance system 106 may be provided with a communication interface 302 arranged to communicate over the communication system 104 with a plurality 1021 , 1022 , 1023 , . . . , 102N and optionally with any other data system . Communication interface 106 may represent any device(s) and functionality that may be used for communication in each particular application. Data received from a plurality of equipment 1021 , 1022 , 1023 , . . . , 102N may be collected into an equipment-specific historical database 306 . Database 306 may contain usage, diagnostic, and/or environmental data collected for each particular piece of equipment over an extended period of time, preferably over the life of the piece of equipment. The data collection system 304 shown in FIG. 3 can generally represent any device(s) and functionality that can be used in data collection.
集中式维护系统106可以进一步包括客户特定的数据库310，客户特定的数据库310可以包含针对每个客户的装备配置数据、客户偏好、设计的使用配置文件等。配置数据可以包括装备类型及其组件。集中式维护系统106还可以进一步包括包含每个类型的装备的参数和特征的装备类型数据库308。例如，数据库308可以包含每个类型的装备和/或其组件的可靠性数据。可靠性是描述以下特性的特征：在规定限制内利用无故障操作执行所需功能的能力、耐久性、可维护性、存储能力以及可运输性或者这些特征的结合。针对可靠性，存在若干众所周知的测量。例如，平均故障前时间(MTTF)指示到系统或者装置发生故障为止前的平均时间。MTTF可以通过将一组相似物体的总服务时间除以该组内的总故障次数来估计。平均故障间隔时间(MTBF)可以通过将总工作时间除以相似物体的组内的故障次数来估计。在连续工作周期之间可能存在修理或者维修动作。故障率指示每单位时间的故障概率。它是故障的发生率。作为进一步的替代，可以利用分布函数或者概率函数来指示到故障为止前或者在故障之间的大概时间。可以将起重机视为由具有不同寿命跨度和可靠性的独立部分或组件组成的串联系统。串联系统的主要特性在于：如果任何子系统或组件未正常工作，则导致整个系统功能丧失。由此，可以针对起重机的个体组件提供可靠性数据。还可以对不同环境数据提供可靠性数据，即，可以指示可靠性与环境的相关性。应该了解，数据库306、308和310可以在个体数据库、虚拟数据库、单个统一数据库、分布式数据库、其任何结合、或者在适用于特定应用的任何其它数据库架构中实现。The centralized maintenance system 106 may further include a customer-specific database 310 that may contain equipment configuration data, customer preferences, designed usage profiles, etc. for each customer. Configuration data may include equipment types and their components. The centralized maintenance system 106 may further include an equipment type database 308 containing parameters and characteristics of each type of equipment. For example, database 308 may contain reliability data for each type of equipment and/or components thereof. Reliability is a characteristic describing the ability to perform a desired function with trouble-free operation within specified limits, durability, maintainability, storage capacity, and transportability, or a combination of these characteristics. There are several well-known measures for reliability. For example, mean time to failure (MTTF) indicates the mean time until a system or device fails. MTTF can be estimated by dividing the total service time of a group of similar objects by the total number of failures within the group. The mean time between failures (MTBF) can be estimated by dividing the total operating time by the number of failures within a group of similar objects. There may be repair or maintenance actions between successive duty cycles. The failure rate indicates the probability of failure per unit time. It is the incidence of failure. As a further alternative, a distribution function or a probability function may be utilized to indicate the approximate time until or between failures. A crane can be thought of as a tandem system made up of individual parts or components with different life spans and reliability. The main characteristic of series systems is that if any subsystem or component fails to function properly, the entire system will lose function. Thereby reliability data can be provided for individual components of the crane. Reliability data may also be provided for different environment data, ie may indicate how reliability depends on the environment. It should be appreciated that databases 306, 308, and 310 may be implemented in individual databases, virtual databases, a single consolidated database, distributed databases, any combination thereof, or in any other database architecture suitable for a particular application.
集中式维护系统106可以进一步包括计算系统312，其被配置为对收集的和存储的信息执行分析、执行仿真并且执行预测性维护的最优化。计算系统312可以利用任何类型的计算架构实现，例如实现在单个计算机中或者分布式计算机系统中。The centralized maintenance system 106 may further include a computing system 312 configured to perform analysis on collected and stored information, perform simulations, and perform optimization of predictive maintenance. Computing system 312 may be implemented using any type of computing architecture, such as implemented in a single computer or in a distributed computer system.
分析部314可以被配置为分析并且处理在数据库306中的装备特定的使用、诊断和/或环境数据，以及在数据库308中的装备类型数据和在数据库310中的客户特定的数据。分析部314可以从数据库306取回数据从而将该信息汇编到对客户和/或维护人员实时可用的客户报告中。由此，因为可以捕捉过载、紧急停止和其它安全问题并且明确引起客户和维护人员对此的注意，所以增加了安全性。更进一步地，分析部314可以分析并且检测装备和/或组件的故障，并且向客户和/或维护人员生成警报。分析部314还可以从客户数据库310或其它来源接收关于检测到的故障和/或执行的维护动作的信息。分析部314可以基于收集到的历史数据、检测到的故障和执行的维护动作来更新在装备类型数据库中的不同类型的装备和组件的可靠性数据。更一般地说，可以基于由多个(例如整个机群)装备提供的信息来更新针对不同类型的装备和组件的可靠性数据和/或维护需要数据，从而使得可以利用提供的信息来预测并且最优化个体装备的维护。换言之，维护服务提供方能够从更多数量的装备搜集信息和经验并且利用收集到的信息来最优化个体装备的本地维护。图6示出更新的效果。获得在使用时间上的多个测量1…N，直到组件磨损(故障)为止。基于多个测量，可以确定平均使用时间和使用时间的概率函数。我们具有的测量越多，就获得更准确的平均使用时间和更准确的概率函数。Analysis section 314 may be configured to analyze and process equipment-specific usage, diagnostic and/or environmental data in database 306 , as well as equipment-type data in database 308 and customer-specific data in database 310 . Analysis section 314 may retrieve data from database 306 to compile this information into customer reports that are available to customers and/or maintenance personnel in real time. Thereby, safety is increased because overloads, emergency stops and other safety problems can be caught and clearly brought to the attention of customers and maintenance personnel. Still further, the analysis section 314 may analyze and detect failures of equipment and/or components, and generate alerts to customers and/or maintenance personnel. Analysis section 314 may also receive information about detected faults and/or performed maintenance actions from customer database 310 or other sources. The analysis section 314 may update reliability data for different types of equipment and components in the equipment type database based on collected historical data, detected faults, and performed maintenance actions. More generally, reliability data and/or maintenance need data for different types of equipment and components can be updated based on information provided by multiple (e.g., entire fleet) equipment, so that the provided information can be used to predict and optimize Optimize the maintenance of individual equipment. In other words, the maintenance service provider is able to gather information and experience from a greater number of equipment and utilize the gathered information to optimize the local maintenance of individual equipment. Figure 6 shows the effect of the update. Multiple measurements 1...N over time of use are obtained until the component wears out (failure). Based on the plurality of measurements, an average usage time and a probability function of the usage time can be determined. The more measurements we have, the more accurate the average usage time and the more accurate the probability function we get.
图4是示出提供针对特定装备和特定客户的最优化的服务或者维护计划的示例的流程图。维护计划/程序可以将以下纳入考虑，例如：装备现状、装备类型特征、环境因素、客户偏好、计划的使用配置文件。FIG. 4 is a flowchart illustrating an example of providing an optimized service or maintenance plan for specific equipment and for a specific customer. Maintenance plans/procedures may take into account eg: equipment condition, equipment type characteristics, environmental factors, customer preferences, planned usage profiles.
首先，可以将初始数据集中输入计算系统312的仿真和最优化引擎316。输入的初始数据可以包括从数据库306、308和310取回的数据。由此，最优化将以下纳入考虑，例如，装备现状、装备使用历史、装备类型特征、环境因素、客户偏好、或者计划的使用配置文件。更特别地，可以首先从客户数据库310取回客户特定数据，包括装备类型。那么，可以从历史数据库306取回装备特定数据，并且可以基于客户特定数据从数据库308取回装备类型特定数据。First, initial data can be centrally input into the simulation and optimization engine 316 of the computing system 312 . The initial data entered may include data retrieved from databases 306 , 308 and 310 . Thus, optimization takes into account, for example, equipment current status, equipment usage history, equipment type characteristics, environmental factors, customer preferences, or planned usage profiles. More specifically, customer specific data, including equipment type, may first be retrieved from customer database 310 . Equipment-specific data may then be retrieved from historical database 306 and equipment-type specific data may be retrieved from database 308 based on customer-specific data.
其次，仿真被用于基于取回的数据来估计装备可能会发生什么。仿真和最优化316允许对装备的未来寿命周期和不同替代动作的多方面查看。这在图5中示出，其中示出在装备的未来寿命周期内计划的N个连续维护动作的估计可靠性和估计累计成本。可以考虑多个不同的潜在计划维修动作，并且可以基于特定装备的估计可靠性、估计维护成本和/或估计安全性来比较不同的维护动作和/或其结合的效果。可以选择提供了在成本与可靠性或安全性之间的最佳折衷的维护动作或维护动作的结合。例如，如果将图5所示出的具有成本和可靠性的连续维护动作考虑为获得了最优结果(例如在成本和可靠性之间的最佳折衷)，则可以选择它们作为图4所示的最优化维护计划402。可选地，在通过仿真和最优化引擎316计算最优化维护计划402之后，如果希望的话，可以(例如经由图3所示的用户接口318)手工调整维护计划402。Second, simulations are used to estimate what might happen to the equipment based on the retrieved data. Simulation and optimization 316 allows for a multi-faceted view of the future life cycle of the equipment and different alternative actions. This is illustrated in Figure 5, which shows the estimated reliability and estimated cumulative cost of N consecutive maintenance actions planned over the future life cycle of the equipment. A number of different potential planned maintenance actions may be considered, and the effects of different maintenance actions and/or combinations thereof may be compared based on estimated reliability, estimated maintenance cost, and/or estimated safety of particular equipment. The maintenance action or combination of maintenance actions can be selected that provides the best compromise between cost and reliability or safety. For example, if the continuous maintenance actions with cost and reliability shown in Figure 5 are considered to achieve an optimal result (e.g. the best trade-off between cost and reliability), they can be selected as shown in Figure 4 An optimized maintenance plan 402 for . Optionally, after the optimized maintenance plan 402 is calculated by the simulation and optimization engine 316, the maintenance plan 402 can be adjusted manually (eg, via the user interface 318 shown in FIG. 3) if desired.
于是，可以将得到的维护计划402提供给客户和/或维护服务提供方。这可以包括：将最优化的维护计划402自动输入至企业资源规划(ERP)系统，例如图3所示的系统320。ERP可以对维护人员生成装备特定和组件特定的维护任务/动作406。由此，最优化维护计划控制日常的维护工作。The resulting maintenance plan 402 may then be provided to customers and/or maintenance service providers. This may include automatically inputting the optimized maintenance plan 402 into an enterprise resource planning (ERP) system, such as the system 320 shown in FIG. 3 . The ERP can generate equipment-specific and component-specific maintenance tasks/actions 406 for maintenance personnel. The optimized maintenance plan thus controls the daily maintenance work.
一般而言，根据示例实施例的维护系统可以在硬件(一个或多个设备)、固件(一个或多个设备)、软件(一个或多个模块)或者其结合中实现。针对固件或者软件，可以通过执行本文所描述的功能模块(例如，过程、功能等)实现。软件或者程序代码可以存储在任何适合的处理器/(多个)计算机可读数据存储介质或者(多个)存储单元或数据库中，并且由一个或多个处理器/计算机执行。例如数据库的数据存储介质或存储单元可以在处理器/计算机内部或者在处理器/计算机外部实现，在后一种情况下，如现有技术已知的，可以经由多种部件与处理器/计算机通信地耦合。In general, a maintenance system according to example embodiments may be implemented in hardware (one or more devices), firmware (one or more devices), software (one or more modules), or a combination thereof. For firmware or software, it can be realized by executing the functional modules (eg, procedures, functions, etc.) described herein. Software or program code may be stored in any suitable processor/computer readable data storage medium(s) or memory unit(s) or database and executed by one or more processors/computers. A data storage medium or storage unit such as a database can be implemented internally to the processor/computer or externally to the processor/computer, in which case it can be connected to the processor/computer via various components, as is known in the art. communicatively coupled.
通过本发明实施例的优点，由于可以尽可能准确系统地预测维护需要和推荐动作，所以可以提高维护动作对客户的透明度。集中式维护计划可以基于事实信息并且不依赖于维护人员的主观观点或专长。任何人均可以在不需要知道或熟悉将要被最优化的目标装备和其历史的情况下使用此工具。因为在保持生产运行的同时避免了起重机的意外故障、崩溃和停工，所以最优化的维护计划可以最优化客户装备的生产力。最优化的维护计划减少了停工时间并且使管理服务得到突破。最优化的维护计划减少了总体生产成本，并且使维护成本可管理以及具有更多可预测性。本发明的实施例可以进一步允许针对特定时刻生成理论上的可靠性分析。Through the advantages of the embodiments of the present invention, since maintenance needs and recommended actions can be predicted systematically as accurately as possible, the transparency of maintenance actions to customers can be improved. Centralized maintenance planning can be based on factual information and does not rely on the subjective opinion or expertise of maintenance personnel. Anyone can use this tool without knowledge or familiarity with the target equipment to be optimized and its history. An optimized maintenance schedule optimizes the productivity of customer equipment by avoiding unexpected failures, breakdowns and downtime of cranes while keeping production running. An optimized maintenance plan reduces downtime and enables breakout management services. An optimized maintenance plan reduces overall production costs and makes maintenance costs manageable and more predictable. Embodiments of the present invention may further allow a theoretical reliability analysis to be generated for a particular time instant.
随着技术进步，本发明的概念可以通过多种方式实现，这对于本领域技术人员而言将是显而易见的。本发明及其实施例不限于上文所描述的示例，而是可以在权利要求的范围内变化。It will be obvious to a person skilled in the art that, as technology advances, the inventive concept can be implemented in various ways. The invention and its embodiments are not limited to the examples described above but may vary within the scope of the claims.
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| CN (1) | CN104620268B (en) |
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| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US9826338B2 (en) | 2014-11-18 | 2017-11-21 | Prophecy Sensorlytics Llc | IoT-enabled process control and predective maintenance using machine wearables |
| US20160313216A1 (en) | 2015-04-25 | 2016-10-27 | Prophecy Sensors, Llc | Fuel gauge visualization of iot based predictive maintenance system using multi-classification based machine learning |
| US10599982B2 (en) | 2015-02-23 | 2020-03-24 | Machinesense, Llc | Internet of things based determination of machine reliability and automated maintainenace, repair and operation (MRO) logs |
| US20160245686A1 (en) | 2015-02-23 | 2016-08-25 | Biplab Pal | Fault detection in rotor driven equipment using rotational invariant transform of sub-sampled 3-axis vibrational data |
| US20160245279A1 (en) | 2015-02-23 | 2016-08-25 | Biplab Pal | Real time machine learning based predictive and preventive maintenance of vacuum pump |
| US10648735B2 (en) | 2015-08-23 | 2020-05-12 | Machinesense, Llc | Machine learning based predictive maintenance of a dryer |
| US10613046B2 (en) | 2015-02-23 | 2020-04-07 | Machinesense, Llc | Method for accurately measuring real-time dew-point value and total moisture content of a material |
| US10481195B2 (en) | 2015-12-02 | 2019-11-19 | Machinesense, Llc | Distributed IoT based sensor analytics for power line diagnosis |
| US10638295B2 (en) | 2015-01-17 | 2020-04-28 | Machinesense, Llc | System and method for turbomachinery preventive maintenance and root cause failure determination |
| CN105593864B (en)* | 2015-03-24 | 2020-06-23 | 埃森哲环球服务有限公司 | Analytical device degradation for maintenance device |
| CN104891290A (en)* | 2015-04-29 | 2015-09-09 | 中联重科股份有限公司 | Reminding message sending system, method and device and construction elevator |
| CN105467949A (en)* | 2015-05-19 | 2016-04-06 | 上海谷德软件工程有限公司 | Crane remote monitoring and intelligent maintenance system based on IOT and DSP |
| US9823289B2 (en) | 2015-06-01 | 2017-11-21 | Prophecy Sensorlytics Llc | Automated digital earth fault system |
| WO2017083240A1 (en)* | 2015-11-12 | 2017-05-18 | Diversey, Inc. | Predictive maintenance |
| DE102016008750A1 (en)* | 2016-07-18 | 2018-01-18 | Liebherr-Werk Nenzing Gmbh | Method for estimating an expected lifetime of a component of a machine |
| US10282796B2 (en) | 2017-01-12 | 2019-05-07 | Johnson Controls Technology Company | Building energy storage system with multiple demand charge cost optimization |
| US11010846B2 (en) | 2017-01-12 | 2021-05-18 | Johnson Controls Technology Company | Building energy storage system with multiple demand charge cost optimization |
| US10949777B2 (en) | 2017-06-07 | 2021-03-16 | Johnson Controls Technology Company | Building energy optimization system with economic load demand response (ELDR) optimization |
| US11238547B2 (en) | 2017-01-12 | 2022-02-01 | Johnson Controls Tyco IP Holdings LLP | Building energy cost optimization system with asset sizing |
| US10324483B2 (en) | 2017-01-12 | 2019-06-18 | Johnson Controls Technology Company | Building energy storage system with peak load contribution cost optimization |
| US11061424B2 (en) | 2017-01-12 | 2021-07-13 | Johnson Controls Technology Company | Building energy storage system with peak load contribution and stochastic cost optimization |
| US11847617B2 (en) | 2017-02-07 | 2023-12-19 | Johnson Controls Tyco IP Holdings LLP | Model predictive maintenance system with financial analysis functionality |
| US11900287B2 (en) | 2017-05-25 | 2024-02-13 | Johnson Controls Tyco IP Holdings LLP | Model predictive maintenance system with budgetary constraints |
| BE1025039B1 (en)* | 2017-03-06 | 2018-10-11 | Safety Move Besloten Vennootschap Met Beperkte Aansprakelijkheid | Device for monitoring the safety of industrial rolling stock and its operators |
| US12242259B2 (en) | 2017-05-25 | 2025-03-04 | Tyco Fire & Security Gmbh | Model predictive maintenance system with event or condition based performance |
| US12282324B2 (en) | 2017-05-25 | 2025-04-22 | Tyco Fire & Security Gmbh | Model predictive maintenance system with degradation impact model |
| US11409274B2 (en) | 2017-05-25 | 2022-08-09 | Johnson Controls Tyco IP Holdings LLP | Model predictive maintenance system for performing maintenance as soon as economically viable |
| US11416955B2 (en) | 2017-05-25 | 2022-08-16 | Johnson Controls Tyco IP Holdings LLP | Model predictive maintenance system with integrated measurement and verification functionality |
| US11747800B2 (en) | 2017-05-25 | 2023-09-05 | Johnson Controls Tyco IP Holdings LLP | Model predictive maintenance system with automatic service work order generation |
| US11636429B2 (en) | 2017-05-25 | 2023-04-25 | Johnson Controls Tyco IP Holdings LLP | Model predictive maintenance systems and methods with automatic parts resupply |
| JP7184797B2 (en) | 2017-05-25 | 2022-12-06 | ジョンソン コントロールズ テクノロジー カンパニー | Model predictive maintenance system for building equipment |
| US11120411B2 (en) | 2017-05-25 | 2021-09-14 | Johnson Controls Tyco IP Holdings LLP | Model predictive maintenance system with incentive incorporation |
| CA3005183A1 (en)* | 2017-05-30 | 2018-11-30 | Joy Global Surface Mining Inc | Predictive replacement for heavy machinery |
| US11022947B2 (en) | 2017-06-07 | 2021-06-01 | Johnson Controls Technology Company | Building energy optimization system with economic load demand response (ELDR) optimization and ELDR user interfaces |
| DE102017117637A1 (en)* | 2017-08-03 | 2019-02-07 | Turck Holding Gmbh | Sensor device and method for generating a status signal |
| CN107844631B (en)* | 2017-09-29 | 2021-02-09 | 北京空间机电研究所 | Method for accurately determining extreme working condition of heat flow outside remote sensor full-life cycle orbit |
| JP6462954B1 (en)* | 2017-11-29 | 2019-01-30 | 三菱電機株式会社 | Maintenance planning system and maintenance planning method |
| US10921792B2 (en) | 2017-12-21 | 2021-02-16 | Machinesense Llc | Edge cloud-based resin material drying system and method |
| DE102018203814A1 (en) | 2018-03-13 | 2019-09-19 | Gebhardt Fördertechnik GmbH | Method for, preferably anticipatory, maintenance of an automated conveyor system and corresponding conveyor system |
| SE546188C2 (en)* | 2018-12-07 | 2024-06-25 | Alimak Group Man Ab | A hoist system and methods for operating a plurality of hoists located at a work site |
| EP3696738A1 (en)* | 2019-02-12 | 2020-08-19 | ABB Schweiz AG | Automated maintenance schedule generation method for modular plants |
| DE102019108415A1 (en)* | 2019-04-01 | 2020-10-01 | Pilz Gmbh & Co. Kg | Method for monitoring the vitality of a number of participants in a distributed technical system |
| CN110222424B (en)* | 2019-06-08 | 2022-06-07 | 太原科技大学 | Reliability optimization method of bridge crane main girder based on RBF-NN |
| SE1950690A1 (en)* | 2019-06-10 | 2020-12-11 | Cargotec Sweden Ab | Method performed by a control unit of a cargo container coupling arrangement |
| EP3763653B1 (en)* | 2019-07-12 | 2025-09-03 | KONE Corporation | Method and arrangement |
| EP3763654A1 (en) | 2019-07-12 | 2021-01-13 | KONE Corporation | Method and elevator arrangement |
| US11480360B2 (en) | 2019-08-06 | 2022-10-25 | Johnson Controls Tyco IP Holdings LLP | Building HVAC system with modular cascaded model |
| CN113620191B (en)* | 2020-05-09 | 2024-08-16 | 徐州重型机械有限公司 | Crane operation protection method, device and system and crane |
| US11961052B2 (en)* | 2020-12-15 | 2024-04-16 | Caterpillar Inc. | Systems and methods for wear assessment and part replacement timing optimization |
| JP7402789B2 (en)* | 2020-12-16 | 2023-12-21 | 株式会社日立産機システム | Crane failure diagnosis system |
| CN113361936B (en)* | 2021-06-09 | 2023-06-30 | 中联重科股份有限公司 | Reliability analysis method, device and system for crane |
| EP4201865B1 (en)* | 2021-12-21 | 2024-09-18 | Hiab AB | A working equipment system, and a method of the working equipment system |
| CN115535854B (en)* | 2022-08-24 | 2024-01-19 | 杭州大杰智能传动科技有限公司 | Intelligent maintenance control system for tower crane |
| CN116625665A (en)* | 2023-06-08 | 2023-08-22 | 陕西建设机械股份有限公司 | Bench test method and system for tower crane mechanism |
| CN117416867B (en)* | 2023-12-18 | 2024-03-08 | 河南恒达机电设备有限公司 | Big data intelligent operation and maintenance method and system for crane and cloud platform |
| EP4574738A1 (en)* | 2023-12-19 | 2025-06-25 | Schneider Electric Industries Sas | Method to operate hoisting appliance for accurate predictive maintenance |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101185065A (en)* | 2005-06-30 | 2008-05-21 | 西门子公司 | Methods and tools for optimizing system maintenance |
| CN101273316A (en)* | 2005-09-30 | 2008-09-24 | 卡特彼勒公司 | asset management system |
| WO2011042286A1 (en)* | 2009-10-07 | 2011-04-14 | Optimized Systems And Solutions Limited | Asset management system with asset maintenance planning |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US7406431B2 (en)* | 2000-03-17 | 2008-07-29 | Siemens Aktiengesellschaft | Plant maintenance technology architecture |
| GB0009329D0 (en) | 2000-04-17 | 2000-05-31 | Duffy & Mcgovern Ltd | A system, method and article of manufacture for corrosion risk analysis and for identifying priorities for the testing and/or maintenance of corrosion |
| US6738748B2 (en) | 2001-04-03 | 2004-05-18 | Accenture Llp | Performing predictive maintenance on equipment |
| US7440906B1 (en)* | 2001-09-04 | 2008-10-21 | Accenture Global Services Gmbh | Identification, categorization, and integration of unplanned maintenance, repair and overhaul work on mechanical equipment |
| US20030172002A1 (en) | 2001-03-15 | 2003-09-11 | Spira Mario Cosmas | Menu driven management and operation technique |
| JP2002297710A (en) | 2001-03-29 | 2002-10-11 | Hitachi Ltd | System and method for supporting maintenance plan of power plant |
| US7937280B1 (en) | 2001-04-02 | 2011-05-03 | I2 Technologies Us, Inc. | Planning and scheduling of maintenance, repair, and overhaul services |
| US6745151B2 (en) | 2002-05-16 | 2004-06-01 | Ford Global Technologies, Llc | Remote diagnostics and prognostics methods for complex systems |
| US7584165B2 (en)* | 2003-01-30 | 2009-09-01 | Landmark Graphics Corporation | Support apparatus, method and system for real time operations and maintenance |
| KR100540162B1 (en) | 2003-12-16 | 2005-12-29 | 한국철도기술연구원 | Information system for railway maintenance |
| DE112005003451T5 (en)* | 2005-02-10 | 2008-01-03 | Fujitsu Ltd., Kawasaki | A service system or service method for providing a variety of services, including the diagnosis of a mobile body, and a portable information device for the system |
| US20090037206A1 (en) | 2007-07-31 | 2009-02-05 | Brian Dara Byrne | Method of forecasting maintenance of a machine |
| US9372482B2 (en) | 2010-05-14 | 2016-06-21 | Harnischfeger Technologies, Inc. | Predictive analysis for remote machine monitoring |
| US8463460B2 (en) | 2011-02-18 | 2013-06-11 | Caterpillar Inc. | Worksite management system implementing anticipatory machine control |
| FI126023B (en) | 2012-08-03 | 2016-05-31 | Konecranes Global Oy | Device provided with a sensor |
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101185065A (en)* | 2005-06-30 | 2008-05-21 | 西门子公司 | Methods and tools for optimizing system maintenance |
| CN101273316A (en)* | 2005-09-30 | 2008-09-24 | 卡特彼勒公司 | asset management system |
| WO2011042286A1 (en)* | 2009-10-07 | 2011-04-14 | Optimized Systems And Solutions Limited | Asset management system with asset maintenance planning |
| Publication number | Publication date |
|---|---|
| US9760068B2 (en) | 2017-09-12 |
| CN104620268A (en) | 2015-05-13 |
| FI128899B (en) | 2021-02-26 |
| WO2014044906A1 (en) | 2014-03-27 |
| FI20125964A (en) | 2014-03-20 |
| FI20125964A7 (en) | 2014-03-20 |
| DE112013004572T5 (en) | 2015-06-25 |
| DE112013004572B4 (en) | 2024-03-28 |
| DE112013004572T8 (en) | 2015-08-06 |
| US20150227122A1 (en) | 2015-08-13 |
| Publication | Publication Date | Title |
|---|---|---|
| CN104620268B (en) | Approaches of predictive maintenance and system | |
| KR102334965B1 (en) | Predictive maintenance system for efficient management of factory automation equipment and productivity improvement | |
| CN112727965B (en) | Fault monitoring method and device for brake of coal mining machine | |
| CN106200616B (en) | Periodic decomposition analysis for remote machine monitoring | |
| CN105631577B (en) | Data transmission method, analysis and prediction report method and system for robot | |
| CN101753364B (en) | Equipment status analysis and prediction and resource allocation method and system | |
| US20220284366A1 (en) | Method and system for managing a crane and/or construction site | |
| US12236731B2 (en) | Method for diagnosis and/or maintenance of a transportation system, and software program | |
| KR102278744B1 (en) | Method and apparatus for outputting alarm about abnormal condition of robot | |
| EP3617117B1 (en) | Model development framework for remote monitoring condition-based maintenance | |
| CN101269767A (en) | Maintaining-managing system for elevator | |
| KR20180068102A (en) | Method and server for providing robot fault monitoring prognostic service | |
| JP6525118B2 (en) | Alarm system | |
| CN118723833A (en) | A tower crane intelligent fault monitoring method and device | |
| CN113779838A (en) | An intelligent maintenance method for a hoist spindle device driven by model and data fusion | |
| US20240232739A1 (en) | Method for analysing a construction project, recording assembly, construction device and recording system | |
| TWI380226B (en) | System and method of prognostic analysis and resource planning for apparatu | |
| CN119143018A (en) | Intelligent management method and system for tower crane operation based on digital twin | |
| KR102409863B1 (en) | Method, server and program for providing robot prevention and prediction measure service | |
| CN115224996A (en) | Hoist, hoist system and state estimation device | |
| CN205170196U (en) | Holographic control of hoist operation and early warning device based on UWB | |
| CN117623128A (en) | Hoisting machinery safety monitoring management system | |
| JP2012218886A (en) | Maintenance work management system of elevator | |
| EP4513152A1 (en) | System and method for vibration analysis | |
| US20240391737A1 (en) | Solution for providing condition data of an elevator rope |
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